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I will build custom rag chatbot with langchain and AWS bedrock


About this gig
Enterprise-Grade RAG Chatbots: LangChain, AWS Bedrock and Vector Search
Stop using generic AI that hallucinates. As a Backend Engineer with experience in mission-critical banking systems at NTT DATA, I build secure, scalable, and high-performance Retrieval-Augmented Generation (RAG) solutions that actually understand your proprietary data.
Why trust me?
I do not build simple wrappers. I design robust architectures. My background in production troubleshooting and cloud infrastructure (AWS, OpenShift) ensures your AI is reliable, private, and cost-efficient.
What I Offer:
- Custom RAG Pipeline: LangChain integration with AWS Bedrock (Claude 3.5), OpenAI, or DeepSeek.
- Advanced Vector Search: Implementation of pgvector, Pinecone, or ChromaDB.
- Cloud-Native Backend: Scalable API using FastAPI/Python or Spring Boot/Java.
- Data Intelligence: Smart document processing (PDF, Web, SQL) to minimize hallucinations.
- Production Ready: Clean code, JWT Authentication, and rigorous testing.
Tech Stack: LangChain, AWS (Lambda, Bedrock, S3), Docker, PostgreSQL, Redis.
Message me now to discuss your project. Let us turn your data into an intelligent assistant.
Get to know Abdallah N
Backend Cloud Engineer
- FromMorocco
- Member sinceSep 2024
- Avg. response time1 hour
Languages
English, Arabic, French
FAQ
Project Goal
Please describe your business use case and the problem you want the AI to solve.
Data Sources
What kind of data will the chatbot use? (PDFs, Website URLs, SQL Database, Notion, etc.)
Cloud Access
Do you have an existing AWS or OpenAI account, or do you need me to guide you through the setup?
Integration
Will this be a standalone API or do you need it integrated into an existing platform?

